Electric energy data dynamic management and control system and method

Abstract

The invention relates to the field of electric power management and control, in particular to an electric energy data dynamic management and control system and method.The system comprises an EMS monitoring module, a load power module, a state prediction module, a power transmission balance module and a dynamic response module, the EMS monitoring module is used for obtaining real-time power, the load power module is used for outputting an active power curve, and the state prediction module is used for predicting the state of the power transmission balance module; the state prediction module is used for judging the charging and discharging states of global variables of the EMS, the power transmission balance module is used for performing power transmission balance setting on PCS equipment, and the dynamic reaction module is used for adjusting charging and discharging power output of each PCS. The influence of abnormal current on the PCS and the battery is reduced, the energy utilization efficiency is improved, the energy storage value is released to the maximum extent, the power grid voltage fluctuation is inhibited through an active defense strategy, and the power grid charging accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the field of power management and control, and in particular to a system and method for dynamic management and control of electric energy data. Background Art

[0002] The Electric Energy Management System (EMS) is a comprehensive automated control system used in the power transmission process to control the production, transmission, and distribution of electricity. It includes components such as supervisory control and data acquisition (SCADA), power generation control, and network analysis. It can monitor the status of the power grid in real time, adjust the output of generator sets, and meet power generation demand.

[0003] When the power storage converter (PCS) in the EMS supplies power to the grid, the EMS fails to coordinate the output of the PCS and the new energy inverter in real time. This may cause power to flow backward to unexpected areas due to system configuration or control anomalies, causing power to flow back to the upper grid or back to other loads. This will not only cause problems with grid billing and reduce equipment revenue, but may also trigger circuit overvoltage protection and damage grid equipment.

[0004] Existing technologies protect the normal operation of the PCS by installing a directional protection relay or setting a reverse power protection voltage. However, this requires sophisticated grid monitoring methods. In the context of microgrids such as photovoltaic and wind power, the power output is complex, the PCS discharge fluctuation margin is small, the protection action is not timely enough, and the dynamic anti-backflow effect of the EMS system is poor. Summary of the Invention

[0005] The purpose of the present invention is to provide a system and method for dynamic control of electric energy data to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: an electric energy data dynamic management and control system, comprising: an EMS monitoring module, a load power module, a state prediction module, a power transmission balance module and a dynamic response module;

[0007] The EMS monitoring module is used to obtain the real-time power of the current load side through the electric energy meter and transmit the meter data to the EMS system using the Modbus TCP protocol. The EMS system uses an industrial real-time database to store data, eliminates data noise through sliding average filtering, regularly collects circuit instantaneous power, and dynamically adjusts the EMS sampling frequency according to the load fluctuation rate. The load power data in the global variable of the power grid is obtained based on the instantaneous power cycle;

[0008] The load power module is used to transform the load power data, decompose the harmonic components and fundamental components in the power curve, determine the circuit active power, calibrate the power offset, correct the power factor angle, and output the corrected active power curve;

[0009] The state prediction module is used to determine the stability of active power based on the historical power curve, dynamically update the maximum error threshold based on the autocorrelation coefficient, standard deviation and confidence interval of the historical data, and calculate the power reference value based on the historical data. When the deviation between the active power and the power reference value exceeds the maximum error threshold of the predetermined charge or discharge for a period of time, it is determined that the EMS global variable is in the charging or discharging state. At the same time, the power trend is predicted according to the integrated LSTM / ARIMA model to predict the charge and discharge state of the EMS system global variable in the next cycle.

[0010] The power transmission balance module is used to define a global variable structure, including power values ​​and timestamps. When the global variable is in the charging or discharging state, the instantaneous reverse power of the circuit is calculated according to the active power curve. The power transmission balance setting is performed on the PCS device in the power system according to the instantaneous reverse power. At the same time, the PCS register address and CAN frame data are parsed to update the PCS device status flag.

[0011] The dynamic response module is used to determine the numerical relationship between the instantaneous reverse power in the global variable and the sum of the maximum discharge power currently set for all PCSs when the global variable is in the charging or discharging state, calculate the charge and discharge power output of each PCS register according to the numerical relationship, set the power output status of all PCSs in the current cycle and the next cycle, and monitor the PCS battery at the same time. When the charge and discharge capacity exceeds the risk value, disconnect it, thereby completing the power synchronization of the load-side PCS in the current cycle.

[0012] Furthermore, the EMS monitoring module includes: an energy metering unit, a data cleaning unit and an interface communication unit;

[0013] The electric energy metering unit is used to obtain instantaneous load power through the electric energy meter and process the instantaneous load power using an anti-aliasing filter + synchronous sampling technology;

[0014] The data cleaning unit is composed of a database set in the EMS, which is used to store sampled data and eliminate abnormal data through a Kalman filter;

[0015] The interface communication unit is used to connect the electric energy meter, EMS and PCS through a network cable and a network port, and use the ModbusTcp protocol to push data in real time.

[0016] Furthermore, the load power module includes: a power conversion unit and a transformation ratio calibration unit;

[0017] The power conversion unit is used to generate a power curve, and uses windowed wavelet transform or FFT to extract the fundamental and harmonic components in the power;

[0018] The transformation ratio calibration unit is used to calibrate the power offset through the CT / PT transformation ratio, perform moving average on the instantaneous power, and correct the active power.

[0019] Furthermore, the state prediction module includes: a power stabilization unit and a deviation prediction unit;

[0020] The power stabilization unit is used to calculate the autocorrelation coefficient of the historical active power curve using a sliding window to determine the stability of the historical power generation data;

[0021] The deviation prediction unit is used to determine the dynamic charge and discharge threshold, predict the power trend in the next cycle, and adjust the PCS power in advance.

[0022] Furthermore, the power transmission balancing module includes: a global variable unit, a reverse flow judgment unit and a status flag unit;

[0023] The global variable unit is used to define global variables in the EMS and use Redis to store them, displaying circuit power curves, charge and discharge status, and alarm status;

[0024] The reverse flow judgment unit is used to calculate the instantaneous reverse flow power of the circuit according to the overflow of the active power curve within the window;

[0025] The status flag unit is used to determine the charge and discharge status of the PCS register and update the PCS status flag.

[0026] Furthermore, the dynamic response module includes: a variable adjustment unit and a PCS setting unit;

[0027] The variable adjustment unit is used to determine the relationship between the maximum power data of the transformer and the instantaneous reverse current power in the global variable;

[0028] The PCS setting unit is used to set the battery power output of all PCSs according to a numerical relationship.

[0029] A method for dynamic control of electric energy data, comprising the following steps:

[0030] Step S1. The instantaneous load power of the circuit is sampled by the energy meter, and the sampling frequency is dynamically adjusted according to the load fluctuation rate. The sampling results are transmitted to the EMS system. The EMS system defines the global variables of the power grid, cyclically obtains the instantaneous load power from the global variables of the power grid, and outputs a discrete power curve. The EMS is an electric energy management system;

[0031] Step S2. Process the discrete power curve using a windowed wavelet transform or FFT transform to extract the fundamental and harmonic components, and obtain the active power curve after correcting the power factor angle;

[0032] Step S3. Calculate the maximum error threshold between the power reference value and the charge and discharge based on the historical power data, and determine whether the active power exceeds the error interval to obtain the charge and discharge status of the global variable;

[0033] Step S4. When the global variable is in the charging or discharging state, the instantaneous reverse power of the circuit is calculated based on the overflow of the active power curve within the error interval, and battery balancing is set for each PCS device according to the instantaneous reverse power, and the PCS status flag is updated. The PCS is an energy storage converter;

[0034] Step S5. Determine the numerical relationship between the instantaneous reverse power in the global variable and the sum of the maximum discharge power of all PCSs, determine the charge and discharge power output of each PCS battery, set the power output state of all PCSs, and complete the power synchronization of the load-side PCSs in the current cycle.

[0035] Furthermore, step S1 includes:

[0036] Step S11. Obtain instantaneous load power on the load side of the power grid through the power meter using an anti-aliasing filter or synchronous sampling technology. The hardware interface of the power meter is compatible with the communication interface of the EMS and supports Modbus RTU / TCP, DL / T645, IEC 61850 and Modbus TCP protocols;

[0037] Step S12. The energy meter dynamically adjusts the sampling frequency according to the load fluctuation rate, so that the sampling frequency v = v0 + k (P1-P2) / t0, where P1 and P2 are the previous sampling power and the load power obtained in the current sampling, respectively, t0 is the previous sampling interval, v0 is the basic sampling frequency, and k is the preset fluctuation adjustment coefficient;

[0038] Step S13. After each sampling, the sampling results are uploaded to the EMS system through the communication port. The EMS system uses an industrial real-time database to store data and eliminates data noise through sliding average filtering. A global variable structure is defined in the EMS system. The global variable contains power values ​​and timestamps, representing the charging and discharging power of all PCS batteries to the grid;

[0039] The instantaneous load power in the global variable of the power grid is obtained cyclically, stored in the global variable structure, and the relationship between the instantaneous load power and time is fitted in chronological order to obtain a discrete power curve.

[0040] Furthermore, step S2 includes:

[0041] Step S21. Lock the fundamental frequency through the phase-locked loop, synchronously obtain voltage and current data through the electric energy meter, perform windowed wavelet transform or FFT transform on the discrete power curve, and calculate the initial active power:

[0042]

[0043] Where Pw is the initial active power, h is the harmonic number, H is the total harmonic number, V h and I h are the voltage and current of the hth harmonic respectively, θ h is the phase difference between voltage and current in the hth harmonic;

[0044] Step S22: calibrate the power offset by the CT / PT ratio, perform a moving average on the fundamental component to obtain the calibrated active power Pu, and fit the active power of each sampling point in the time domain to obtain the active power curve Pu(t).

[0045] Furthermore, step S3 includes:

[0046] Step S31. Input the historical power data into a digital modeling tool to determine the mean, autocorrelation coefficient, and standard deviation of the historical data. The rolling window period is determined based on the autocorrelation coefficient of the historical data. The rolling window period is the length of the rolling window when the autocorrelation coefficient reaches its maximum value.

[0047] Step S32. Using the mean of the active power curve within the rolling window period as the power reference value, and within a 90%-95% confidence limit, determine the maximum error thresholds for charging and discharging, such that the probability that the power within the rolling window period is within the error interval [P0-w1, P0+w2] exceeds the confidence limit, where P0 is the power reference value, w1 is the global variable maximum error threshold for charging, and w2 is the maximum error threshold for discharging;

[0048] Step S33. Continuously monitor the active power curve. When the active power curve is higher than the upper limit of the error interval, determine that the global variable is in a discharging state. When the active power curve is lower than the lower limit of the error interval, determine that the global variable is in a charging state.

[0049] Furthermore, step S4 includes:

[0050] Step S41. When the global variable is in the charging state, the instantaneous reverse power of the circuit is the lower bound of the error interval minus the instantaneous load power. When the global variable is in the discharging state, the instantaneous reverse power of the circuit is the instantaneous load power minus the upper bound of the error interval.

[0051] Step S42: Perform power transmission balance setting for PCS equipment in the power system according to the instantaneous reverse power, parse the PCS register address and CAN frame data, and update the PCS equipment status flag.

[0052] Furthermore, step S5 includes:

[0053] Step S51: Determine the charge and discharge power output of the PCS battery:

[0054] When the global variable is in the discharge state, determine whether the instantaneous reverse flow power in the global variable is greater than the sum of the maximum discharge powers of all PCSs. If so, set the discharge power of all PCSs to the maximum discharge power. If not, set the discharge power of all PCSs to the instantaneous reverse flow power / the number of PCSs.

[0055] When the global variable is in the charging state, determine whether the difference between the maximum power of the circuit transformer and the instantaneous load power is greater than the sum of the maximum discharge powers set for all PCSs. If so, set the discharge power of all PCSs to the maximum discharge power. If not, set the charging power of all PCSs to the difference between the maximum power of the transformer and the instantaneous load power / the number of PCSs.

[0056] Step S52: Set the power output status of all PCSs to complete the power synchronization of the load-side PCSs in the current cycle.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] 1. The present invention obtains the real-time power of the current load side through the electric energy meter and transmits it to the EMS system. It obtains the load power data in the global variable for the real-time power cycle, transforms the load power data, determines the active power of the circuit, and thus judges the PCS power direction. The control mode of the PCS is adjusted in advance to prevent the reverse current from impacting the power equipment and avoid the problem of reverse power supply in the power system.

[0059] 2. The present invention introduces the stability of active power based on historical records, calculates the autocorrelation coefficient and the maximum error range, judges and predicts the charge and discharge status of the global variable based on the deviation between the active power and the maximum error range, sets PCS equipment in the power system to balance power transmission, accurately controls the discharge timing, optimizes energy storage benefits, reduces the impact of abnormal current on PCS and batteries, improves energy utilization efficiency, maximizes the release of energy storage value, and avoids technical risks.

[0060] 3. Based on the circuit charge and discharge status, the present invention determines whether the load power data in the global variable is greater than the sum of the maximum charge and discharge powers currently set for all PCSs, thereby setting the discharge power of all PCSs. This prevents energy storage from participating in peak-valley arbitrage due to reverse flow interruption. Through the active defense strategy of the EMS, precise matching of energy storage, photovoltaics, and loads is achieved, suppressing grid voltage fluctuations and improving grid billing accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0062] Figure 1 This is a structural diagram of a dynamic control system for electric energy data according to the present invention;

[0063] Figure 2 It is a schematic diagram of the steps of a method for dynamic control of electric energy data of the present invention. DETAILED DESCRIPTION

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0065] See also Figure 1 , the present invention provides a technical solution: an electric energy data dynamic management and control system, including: an EMS monitoring module, a load power module, a state prediction module, a power transmission balance module and a dynamic response module;

[0066] The EMS monitoring module is used to obtain the real-time power of the current load side through the electric energy meter and transmit the meter data to the EMS system using the Modbus TCP protocol. The EMS system uses an industrial real-time database to store data, eliminates data noise through sliding average filtering, regularly collects circuit instantaneous power, and dynamically adjusts the EMS sampling frequency according to the load fluctuation rate. The load power data in the global variable of the power grid is obtained based on the instantaneous power cycle;

[0067] The EMS monitoring module includes: an energy metering unit, a data cleaning unit and an interface communication unit;

[0068] The electric energy metering unit is used to obtain instantaneous load power through the electric energy meter and process the instantaneous load power using an anti-aliasing filter + synchronous sampling technology;

[0069] The data cleaning unit is composed of a database set in the EMS, which is used to store sampled data and eliminate abnormal data through a Kalman filter;

[0070] The interface communication unit is used to connect the electric energy meter, EMS and PCS through a network cable and a network port, and use the ModbusTcp protocol to push data in real time.

[0071] The load power module is used to transform the load power data, decompose the harmonic components and fundamental components in the power curve, determine the circuit active power, calibrate the power offset, correct the power factor angle, and output the corrected active power curve;

[0072] The load power module includes: a power conversion unit and a transformation ratio calibration unit;

[0073] The power conversion unit is used to generate a power curve, and uses windowed wavelet transform or FFT to extract the fundamental and harmonic components in the power;

[0074] The transformation ratio calibration unit is used to calibrate the power offset through the CT / PT transformation ratio, perform moving average on the instantaneous power, and correct the active power.

[0075] The state prediction module is used to determine the stability of active power based on the historical power curve, dynamically update the maximum error threshold based on the autocorrelation coefficient, standard deviation and confidence interval of the historical data, and calculate the power reference value based on the historical data. When the deviation between the active power and the power reference value exceeds the maximum error threshold of the predetermined charge or discharge for a period of time, it is determined that the EMS global variable is in the charging or discharging state. At the same time, the power trend is predicted according to the integrated LSTM / ARIMA model to predict the charge and discharge state of the EMS system global variable in the next cycle.

[0076] The state prediction module includes: a power stabilization unit and a deviation prediction unit;

[0077] The power stabilization unit is used to calculate the autocorrelation coefficient of the historical active power curve using a sliding window to determine the stability of the historical power generation data;

[0078] The deviation prediction unit is used to determine the dynamic charge and discharge threshold, predict the power trend in the next cycle, and adjust the PCS power in advance.

[0079] The power transmission balance module is used to define a global variable structure, including power values ​​and timestamps. When the global variable is in the charging or discharging state, the instantaneous reverse power of the circuit is calculated according to the active power curve. The power transmission balance setting is performed on the PCS device in the power system according to the instantaneous reverse power. At the same time, the PCS register address and CAN frame data are parsed to update the PCS device status flag.

[0080] The power transmission balance module includes: a global variable unit, a reverse flow judgment unit and a status flag unit;

[0081] The global variable unit is used to define global variables in the EMS and use Redis to store them, displaying circuit power curves, charge and discharge status, and alarm status;

[0082] The reverse flow judgment unit is used to calculate the instantaneous reverse flow power of the circuit according to the overflow of the active power curve within the window;

[0083] The status flag unit is used to determine the charge and discharge status of the PCS register and update the PCS status flag.

[0084] The dynamic response module is used to determine the numerical relationship between the instantaneous reverse power in the global variable and the sum of the maximum discharge power currently set for all PCSs when the global variable is in the charging or discharging state, calculate the charge and discharge power output of each PCS register according to the numerical relationship, set the power output status of all PCSs in the current cycle and the next cycle, and monitor the PCS battery at the same time. When the charge and discharge capacity exceeds the risk value, disconnect it, thereby completing the power synchronization of the load-side PCS in the current cycle.

[0085] The dynamic response module includes: a variable adjustment unit and a PCS setting unit;

[0086] The variable adjustment unit is used to determine the relationship between the maximum power data of the transformer and the instantaneous reverse current power in the global variable;

[0087] The PCS setting unit is used to set the battery power output of all PCSs according to a numerical relationship.

[0088] like Figure 2 As shown, a method for dynamic control of electric energy data includes the following steps:

[0089] Step S1. The instantaneous load power of the circuit is sampled by the energy meter, and the sampling frequency is dynamically adjusted according to the load fluctuation rate. The sampling results are transmitted to the EMS system. The EMS system defines the global variables of the power grid, cyclically obtains the instantaneous load power from the global variables of the power grid, and outputs a discrete power curve. The EMS is an electric energy management system;

[0090] Step S1 includes:

[0091] Step S11. Obtain instantaneous load power on the load side of the power grid through the power meter using an anti-aliasing filter or synchronous sampling technology. The hardware interface of the power meter is compatible with the communication interface of the EMS and supports Modbus RTU / TCP, DL / T645, IEC 61850 and Modbus TCP protocols;

[0092] Step S12. The energy meter dynamically adjusts the sampling frequency according to the load fluctuation rate, so that the sampling frequency v = v0 + k (P1-P2) / t0, where P1 and P2 are the previous sampling power and the load power obtained in the current sampling, respectively, t0 is the previous sampling interval, v0 is the basic sampling frequency, and k is the preset fluctuation adjustment coefficient;

[0093] Step S13. After each sampling, the sampling results are uploaded to the EMS system through the communication port. The EMS system uses an industrial real-time database to store data and eliminates data noise through sliding average filtering. A global variable structure is defined in the EMS system. The global variable contains power values ​​and timestamps, representing the charging and discharging power of all PCS batteries to the grid;

[0094] The instantaneous load power in the global variable of the power grid is obtained cyclically, stored in the global variable structure, and the relationship between the instantaneous load power and time is fitted in chronological order to obtain a discrete power curve.

[0095] Step S2. Process the discrete power curve using a windowed wavelet transform or FFT transform to extract the fundamental and harmonic components, and obtain the active power curve after correcting the power factor angle;

[0096] Step S2 includes:

[0097] Step S21. Lock the fundamental frequency through the phase-locked loop, synchronously obtain voltage and current data through the electric energy meter, perform windowed wavelet transform or FFT transform on the discrete power curve, and calculate the initial active power:

[0098]

[0099] Where Pw is the initial active power, h is the harmonic number, H is the total harmonic number, V h and I h are the voltage and current of the hth harmonic respectively, θ h is the phase difference between voltage and current in the hth harmonic;

[0100] Step S22: calibrate the power offset by the CT / PT ratio, perform a moving average on the fundamental component to obtain the calibrated active power Pu, and fit the active power of each sampling point in the time domain to obtain the active power curve Pu(t).

[0101] Step S3. Calculate the maximum error threshold between the power reference value and the charge and discharge based on the historical power data, and determine whether the active power exceeds the error interval to obtain the charge and discharge status of the global variable;

[0102] Step S3 includes:

[0103] Step S31. Input the historical power data into a digital modeling tool to determine the mean, autocorrelation coefficient, and standard deviation of the historical data. The rolling window period is determined based on the autocorrelation coefficient of the historical data. The rolling window period is the length of the rolling window when the autocorrelation coefficient reaches its maximum value.

[0104] Step S32. Using the mean of the active power curve within the rolling window period as the power reference value, and within a 90%-95% confidence limit, determine the maximum error thresholds for charging and discharging, such that the probability that the power within the rolling window period is within the error interval [P0-w1, P0+w2] exceeds the confidence limit, where P0 is the power reference value, w1 is the global variable maximum error threshold for charging, and w2 is the maximum error threshold for discharging;

[0105] Step S33. Continuously monitor the active power curve. When the active power curve is higher than the upper limit of the error interval, determine that the global variable is in a discharging state. When the active power curve is lower than the lower limit of the error interval, determine that the global variable is in a charging state.

[0106] Step S4. When the global variable is in the charging or discharging state, the instantaneous reverse power of the circuit is calculated based on the overflow of the active power curve within the error interval, and battery balancing is set for each PCS device according to the instantaneous reverse power, and the PCS status flag is updated. The PCS is an energy storage converter;

[0107] Step S4 includes:

[0108] Step S41. When the global variable is in the charging state, the instantaneous reverse power of the circuit is the lower bound of the error interval minus the instantaneous load power. When the global variable is in the discharging state, the instantaneous reverse power of the circuit is the instantaneous load power minus the upper bound of the error interval.

[0109] Step S42: Perform power transmission balance setting for PCS equipment in the power system according to the instantaneous reverse power, parse the PCS register address and CAN frame data, and update the PCS equipment status flag.

[0110] Step S5. Determine the numerical relationship between the instantaneous reverse power in the global variable and the sum of the maximum discharge power of all PCSs, determine the charge and discharge power output of each PCS battery, set the power output state of all PCSs, and complete the power synchronization of the load-side PCSs in the current cycle.

[0111] Step S5 includes:

[0112] Step S51: Determine the charge and discharge power output of the PCS battery:

[0113] When the global variable is in the discharge state, determine whether the instantaneous reverse flow power in the global variable is greater than the sum of the maximum discharge powers of all PCSs. If so, set the discharge power of all PCSs to the maximum discharge power. If not, set the discharge power of all PCSs to the instantaneous reverse flow power / the number of PCSs.

[0114] When the global variable is in the charging state, determine whether the difference between the maximum power of the circuit transformer and the instantaneous load power is greater than the sum of the maximum discharge powers set for all PCSs. If so, set the discharge power of all PCSs to the maximum discharge power. If not, set the charging power of all PCSs to the difference between the maximum power of the transformer and the instantaneous load power / the number of PCSs.

[0115] Step S52: Set the power output status of all PCSs to complete the power synchronization of the load-side PCSs in the current cycle.

[0116] Example: There are three PCSs in the power grid. Every 15ms, the power in the circuit global variable is monitored. The instantaneous reverse power is 3kW, the instantaneous load power is 40kW, and the circuit is in a discharge state. The sum of the maximum discharge power of the three PCSs is 6kW. The Modbus TCP protocol is used to send the 06 function code to the three PCSs to set the discharge power of the three PCSs to 1kW.

[0117] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0118] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for dynamic control of electric energy data, characterized in that: The method comprises the following steps: Step S1. The instantaneous load power of the circuit is sampled by the energy meter, and the sampling frequency is dynamically adjusted according to the load fluctuation rate. The sampling results are transmitted to the EMS system. The EMS system defines the global variables of the power grid, cyclically obtains the instantaneous load power from the global variables of the power grid, and outputs a discrete power curve. The EMS is an electric energy management system; Step S2. Process the discrete power curve using a windowed wavelet transform or FFT transform to extract the fundamental and harmonic components, and obtain the active power curve after correcting the power factor angle; Step S3. Calculate the maximum error threshold between the power reference value and the charge and discharge based on the historical power data, and determine whether the active power exceeds the error interval to obtain the charge and discharge status of the global variable; Step S4. When the global variable is in the charging or discharging state, the instantaneous reverse power of the circuit is calculated based on the overflow of the active power curve within the error interval, and battery balancing is set for each PCS device according to the instantaneous reverse power, and the PCS status flag is updated. The PCS is an energy storage converter; Step S5. Determine the numerical relationship between the instantaneous reverse power in the global variable and the sum of the maximum discharge power of all PCSs, determine the charge and discharge power output of each PCS battery, set the power output state of all PCSs, and complete the power synchronization of the load-side PCSs in the current cycle.

2. The method for dynamic control of electric energy data according to claim 1, characterized in that: Step S1 includes: Step S11. Obtain the instantaneous load power on the load side of the power grid through the electric energy meter using an anti-aliasing filter or synchronous sampling technology. The hardware interface of the electric energy meter is compatible with the communication interface of the EMS and supports Modbus RTU / TCP, DL / T645, IEC61850 and Modbus Tcp protocols; Step S12. The energy meter dynamically adjusts the sampling frequency according to the load fluctuation rate, so that the sampling frequency v = v0 + k (P1-P2) / t0, where P1 and P2 are the previous sampling power and the load power obtained in the current sampling, respectively, t0 is the previous sampling interval, v0 is the basic sampling frequency, and k is the preset fluctuation adjustment coefficient; Step S13. After each sampling, the sampling results are uploaded to the EMS system through the communication port. The EMS system uses an industrial real-time database to store data and eliminates data noise through sliding average filtering. A global variable structure is defined in the EMS system. The global variable contains power values ​​and timestamps, representing the charging and discharging power of all PCS batteries to the grid; The instantaneous load power in the global variable of the power grid is obtained cyclically, stored in the global variable structure, and the relationship between the instantaneous load power and time is fitted in chronological order to obtain a discrete power curve.

3. The method for dynamic control of electric energy data according to claim 2, characterized in that: Step S2 includes: Step S21. Lock the fundamental frequency through the phase-locked loop, synchronously obtain voltage and current data through the electric energy meter, perform windowed wavelet transform or FFT transform on the discrete power curve, and calculate the initial active power: Where Pw is the initial active power, h is the harmonic number, H is the total harmonic number, V h and I h are the voltage and current of the hth harmonic respectively, θ h is the phase difference between voltage and current in the hth harmonic; Step S22: calibrate the power offset by the CT / PT ratio, perform a moving average on the fundamental component to obtain the calibrated active power Pu, and fit the active power of each sampling point in the time domain to obtain the active power curve Pu(t).

4. The method for dynamic control of electric energy data according to claim 3, characterized in that: Step S3 includes: Step S31. Input the historical power data into a digital modeling tool to determine the mean, autocorrelation coefficient, and standard deviation of the historical data. The rolling window period is determined based on the autocorrelation coefficient of the historical data. The rolling window period is the length of the rolling window when the autocorrelation coefficient reaches its maximum value. Step S32. Using the mean of the active power curve within the rolling window period as the power reference value, and within a 90%-95% confidence limit, determine the maximum error thresholds for charging and discharging, such that the probability that the power within the rolling window period is within the error interval [P0-w1, P0+w2] exceeds the confidence limit, where P0 is the power reference value, w1 is the global variable maximum error threshold for charging, and w2 is the maximum error threshold for discharging; Step S33. Continuously monitor the active power curve. When the active power curve is higher than the upper limit of the error interval, determine that the global variable is in a discharging state. When the active power curve is lower than the lower limit of the error interval, determine that the global variable is in a charging state.

5. The method for dynamic control of electric energy data according to claim 4, characterized in that: Step S4 includes: Step S41. When the global variable is in the charging state, the instantaneous reverse power of the circuit is the lower bound of the error interval minus the instantaneous load power. When the global variable is in the discharging state, the instantaneous reverse power of the circuit is the instantaneous load power minus the upper bound of the error interval. Step S42. Perform power balance settings on the PCS device in the power system according to the instantaneous reverse power, parse the PCS register address and CAN frame data, and update the PCS device status flag; Step S5 includes: Step S51: Determine the charge and discharge power output of the PCS battery: When the global variable is in the discharge state, determine whether the instantaneous reverse flow power in the global variable is greater than the sum of the maximum discharge powers of all PCSs. If so, set the discharge power of all PCSs to the maximum discharge power. If not, set the discharge power of all PCSs to the instantaneous reverse flow power / the number of PCSs. When the global variable is in the charging state, determine whether the difference between the maximum power of the circuit transformer and the instantaneous load power is greater than the sum of the maximum discharge powers set for all PCSs. If so, set the discharge power of all PCSs to the maximum discharge power. If not, set the charging power of all PCSs to the difference between the maximum power of the transformer and the instantaneous load power / the number of PCSs. Step S52: Set the power output status of all PCSs to complete the power synchronization of the load-side PCSs in the current cycle.

6. A dynamic control system for electric energy data, characterized in that: The system includes the following modules: EMS monitoring module, load power module, state prediction module, power transmission balance module and dynamic response module; The EMS monitoring module is used to obtain the real-time power of the current load side through the electric energy meter and transmit the meter data to the EMS system using the Modbus TCP protocol. The EMS system uses an industrial real-time database to store data, eliminates data noise through sliding average filtering, regularly collects circuit instantaneous power, and dynamically adjusts the EMS sampling frequency according to the load fluctuation rate. The load power data in the global variable of the power grid is obtained based on the instantaneous power cycle; The load power module is used to transform the load power data, decompose the harmonic components and fundamental components in the power curve, determine the circuit active power, calibrate the power offset, correct the power factor angle, and output the corrected active power curve; The state prediction module is used to determine the stability of active power based on the historical power curve, dynamically update the maximum error threshold based on the autocorrelation coefficient, standard deviation and confidence interval of the historical data, and calculate the power reference value based on the historical data. When the deviation between the active power and the power reference value exceeds the maximum error threshold of the predetermined charge or discharge for a period of time, it is determined that the EMS global variable is in the charging or discharging state. At the same time, the power trend is predicted according to the integrated LSTM / ARIMA model to predict the charge and discharge state of the EMS system global variable in the next cycle. The power transmission balance module is used to define a global variable structure, including power values ​​and timestamps. When the global variable is in the charging or discharging state, the instantaneous reverse power of the circuit is calculated according to the active power curve. The power transmission balance setting is performed on the PCS device in the power system according to the instantaneous reverse power. At the same time, the PCS register address and CAN frame data are parsed to update the PCS device status flag. The dynamic response module is used to determine the numerical relationship between the instantaneous reverse power in the global variable and the sum of the maximum discharge power currently set for all PCSs when the global variable is in the charging or discharging state, calculate the charge and discharge power output of each PCS register according to the numerical relationship, set the power output status of all PCSs in the current cycle and the next cycle, and monitor the PCS battery at the same time. When the charge and discharge capacity exceeds the risk value, disconnect it, thereby completing the power synchronization of the load-side PCS in the current cycle.

7. The electric energy data dynamic management and control system according to claim 6, characterized in that: The EMS monitoring module includes: an energy metering unit, a data cleaning unit and an interface communication unit; The electric energy metering unit is used to obtain instantaneous load power through the electric energy meter and process the instantaneous load power using an anti-aliasing filter + synchronous sampling technology; The data cleaning unit is composed of a database set in the EMS, which is used to store sampled data and eliminate abnormal data through a Kalman filter; The interface communication unit is used to connect the electric energy meter, EMS and PCS through a network cable and a network port, and use the Modbus TCP protocol to push data in real time.

8. The electric energy data dynamic management and control system according to claim 7, characterized in that: The load power module includes: a power conversion unit and a transformation ratio calibration unit; The power conversion unit is used to generate a power curve, and uses windowed wavelet transform or FFT to extract the fundamental and harmonic components in the power; The transformation ratio calibration unit is used to calibrate the power offset through the CT / PT transformation ratio, perform a moving average on the instantaneous power, and correct the active power; The state prediction module includes: a power stabilization unit and a deviation prediction unit; The power stabilization unit is used to calculate the autocorrelation coefficient of the historical active power curve using a sliding window to determine the stability of the historical power generation data; The deviation prediction unit is used to determine the dynamic charge and discharge threshold, predict the power trend in the next cycle, and adjust the PCS power in advance.

9. The electric energy data dynamic management and control system according to claim 8, characterized in that: The power transmission balance module includes: a global variable unit, a reverse flow judgment unit and a status flag unit; The global variable unit is used to define global variables in the EMS and use Redis to store them, displaying circuit power curves, charge and discharge status, and alarm status; The reverse flow judgment unit is used to calculate the instantaneous reverse flow power of the circuit according to the overflow of the active power curve within the window; The status flag unit is used to determine the charge and discharge status of the PCS register and update the PCS status flag.

10. The electric energy data dynamic management and control system according to claim 9, characterized in that: The dynamic response module includes: a variable adjustment unit and a PCS setting unit; The variable adjustment unit is used to determine the relationship between the maximum power data of the transformer and the instantaneous reverse current power in the global variable; The PCS setting unit is used to set the battery power output of all PCSs according to a numerical relationship.

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